Building Claude Agents

Overview

Building agents with Claude involves creating an agentic loop where Claude receives a task, decides which tools to use, calls them, processes the results, and iterates until the task is complete. This pattern enables Claude to interact with external systems, process data, and complete multi-step tasks autonomously.

The foundation is Claude’s tool use capability: you define tools with names, descriptions, and JSON Schema input specifications. Claude decides when and how to call these tools based on the conversation context and its instructions. The agentic loop feeds tool results back to Claude, which then decides whether to call more tools or provide a final response.

Effective agent design requires careful system prompt engineering to guide Claude’s behavior, appropriate tool definitions that give Claude the right capabilities, and guard rails to prevent unintended actions.

When to Use

Build Claude agents when you need autonomous task completion that requires interacting with external systems (APIs, databases, file systems). Start simple with a few tools and expand the agent’s capabilities iteratively.

Getting Started

import Anthropic from '@anthropic-ai/sdk'

const tools = [{
  name: 'get_weather',
  description: 'Get the current weather for a location',
  input_schema: {
    type: 'object' as const,
    properties: { location: { type: 'string' } },
    required: ['location']
  }
}]

const client = new Anthropic()
// Run the agentic loop
let messages = [{ role: 'user' as const, content: 'What is the weather in Tokyo?' }]

while (true) {
  const response = await client.messages.create({
    model: 'claude-sonnet-4-5-20250929', max_tokens: 1024, tools, messages
  })
  if (response.stop_reason === 'end_turn') break
  // Process tool calls and continue...
}